Integrated Wireless Neural
Recording System for
Neuroprosthetics and Advanced
Neuroscience Research
Moo Sung Chae
Integrat...
Overview
 Neural Recording Systems
 Motivations
 Design Issues
 Noise
 Optimization
 Wireless
 Prototype Systems an...
 A recording system to monitor neuron’s activities
 Neurons communicate by “action potentials”
 Action potential is an ...
Near field signal
1)  Intra-cellular action potential : rapid change in trans membrane
potential cause by the voltage depe...
Signal Type Bandwidth (Hz) Range (mVpp)
EEG 0.05 ~ 128 0.02 ~ 0.4
ECoG 0.1 ~ 64 0.02 ~ 1
EMG 1 ~ 128 0.02 ~ 1
LFPs 0.1 ~ 1...
 Study of complex neural networks of the animals
in their natural environment
 A large number of recording channels
 To...
Artificial devices to replace or improve the function of an
impaired nervous system
 Upper and lower limb prosthesis [3],...
Challenges
 Simultaneous recording from a large number of
channels (more than 100 channels) [9]
 Untethered wireless tra...
Proposed System
 Design methodology to optimize the power and
area
 Programmable gain and bandwidth of the
amplifiers
 ...
Front-end Blocks
Decide the resolution of ADC
Optimize preamplifier
Decide the number of channel
per one ADC
System resolution
by electrode...
Noise Sources
Neuronal Noise
~ 20µVrms
Tissue/Electrode
Noise
~ 10µVrms
Electronics
Noise
~ 5µVrms
Z. Yang, Q. Zhao, E. Ke...
Neural Signal Processing Engine
UWB
1.  FCC assigned 3.1 ~ 10.6 GHz spectrum for
unlicensed medical and communication
systems.
2.  Short range application...
IR UWB vs Multi-carrier UWB
 Impulse radio (IR) UWB is more suitable than
multi-carrier UWB such as OFDM.
 Use UWB pulse...
UWB Wireless Tx & Rx
H L H L L H H H L
10 01 10 01 01 10 10 10 01 00 00 00 00 00 00 00
serialized 9-bit sampled data Redun...
UWB Prototype
1.  Custom designed TX chip in 0.35µm CMOS process
2.  Manchester coding for clock recovery and channel
sepa...
UWB Prototype Test Results
[Output of CMOS TX] [PSD of the UWB pulse@TX]
[Recovered data@RX]
  Maximum data rate of
90Mbp...
Architecture of Prototype System
Bench Top Test Results
1. Ex-vivo extracellular action potential
recording from a dissected snail
brain (A circumoesophageal ring
dissected from ...
In-vitro Recording
1. Snail neurons were cultured on Ayanda MEAs
2. Electrode impedance is 1MΩ.
3. Recording from a cluste...
1.  4-channel recording IC (cut-down
version of 128ch recording IC)
2.  EEG, ECG, EMG
3.  USB2.0 PC interface
FPGA
USB2.0
...
[A mouse wearing the recording system. Photo was
taken at Arizona State University]
1.  Recording electrode implanted in
a...
Human EEG and ECG Recording
Summary & Acknowledgement
 Need for versatile wireless recording systems for
advanced neuroscience research and
neuroprot...
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Integrated Wireless Neural Recording System for Neuroprosthetics ...

  1. 1. Integrated Wireless Neural Recording System for Neuroprosthetics and Advanced Neuroscience Research Moo Sung Chae Integrated Bioelectronics Group Department of Electrical Engineering University of California, Santa Cruz
  2. 2. Overview  Neural Recording Systems  Motivations  Design Issues  Noise  Optimization  Wireless  Prototype Systems and Test Results  Summary
  3. 3.  A recording system to monitor neuron’s activities  Neurons communicate by “action potentials”  Action potential is an all-or-nothing signal Neural Recording Systems
  4. 4. Near field signal 1)  Intra-cellular action potential : rapid change in trans membrane potential cause by the voltage dependent trans membrane conductance (H-H model) 2)  Extra-cellular action potential : solenoidal current around neurons, few hundred µm 3)  Local field potential (LFP) : coherent low frequency change, a few mm Far field signal 1)  Electrocorticograms (EcoG) : sub-dural 2)  Electroencephalograph (EEG) : on the scalp Neural Signals
  5. 5. Signal Type Bandwidth (Hz) Range (mVpp) EEG 0.05 ~ 128 0.02 ~ 0.4 ECoG 0.1 ~ 64 0.02 ~ 1 EMG 1 ~ 128 0.02 ~ 1 LFPs 0.1 ~ 100 0.1 ~ 1 EAPs 100 ~ 10K 0.04 ~ 0.2 IAPs 100 ~ 10K ~ 100 Neural Signals – Properties Adjustability of the amplifier is necessary
  6. 6.  Study of complex neural networks of the animals in their natural environment  A large number of recording channels  To remove tethering wire  Miniaturized and low power consumption Motivations (1) – Advanced Neuroscience
  7. 7. Artificial devices to replace or improve the function of an impaired nervous system  Upper and lower limb prosthesis [3],[4]  Bladder and bowel movement [5],[6]  Respiration control for SCI patients [7]  Hand grasping [8] Motivations (2) – Neural Prostheses
  8. 8. Challenges  Simultaneous recording from a large number of channels (more than 100 channels) [9]  Untethered wireless transmission of recorded data in free running animals  On-the-fly spike sorting  Programmability and Versatility  Integration and Miniaturization  Low-power consumption
  9. 9. Proposed System  Design methodology to optimize the power and area  Programmable gain and bandwidth of the amplifiers  On-the-fly spike sorting engine  High data rate & Low power transmitter for simultaneous recording of 128 channels (90 Mbps)
  10. 10. Front-end Blocks
  11. 11. Decide the resolution of ADC Optimize preamplifier Decide the number of channel per one ADC System resolution by electrode noise Proposed Architecture Component modeling 1. Fixed design constants 2. Design variables to optimize Design Methodology
  12. 12. Noise Sources Neuronal Noise ~ 20µVrms Tissue/Electrode Noise ~ 10µVrms Electronics Noise ~ 5µVrms Z. Yang, Q. Zhao, E. Keefer and W. Liu, "Noise Characterization, Modeling, and Reduction for In Vivo Neural Recording," to appear in Neural Information Processing Systems (NIPS), 2010.  Biological and interface noise is larger than circuit noise.  Need to optimize the performance of the amplifiers  Different techniques for different noise sources
  13. 13. Neural Signal Processing Engine
  14. 14. UWB 1.  FCC assigned 3.1 ~ 10.6 GHz spectrum for unlicensed medical and communication systems. 2.  Short range applications with large bandwidth 3.  Small antenna size due to high frequency nature
  15. 15. IR UWB vs Multi-carrier UWB  Impulse radio (IR) UWB is more suitable than multi-carrier UWB such as OFDM.  Use UWB pulse for data symbol (telegraph)  Simple CMOS pulse generator for Tx  Low power at Tx, but high power at Rx
  16. 16. UWB Wireless Tx & Rx H L H L L H H H L 10 01 10 01 01 10 10 10 01 00 00 00 00 00 00 00 serialized 9-bit sampled data Redundant data UWB pulse(PPM) Manchester coded data sampled data UWB pulse(OOK) UWB Pulse generator Pulse shaping Filter UWB antenna Encoder OOK modulator PPM modulator dCLK pCLK From ADC MUX Pad & package parastics 9 Encoded data OOKin PPMin Seriallizer data dCLK Mode sel BPF@4GHz LPF@100 MHz LNA stage Diode Lowpass Filter FPGA Analog. AmplifierBPF UWB Antennas
  17. 17. UWB Prototype 1.  Custom designed TX chip in 0.35µm CMOS process 2.  Manchester coding for clock recovery and channel separation@RX 3.  PPM and OOK 4.  Adjustable pulse width 5.  Receiver is implemented using commercial components.
  18. 18. UWB Prototype Test Results [Output of CMOS TX] [PSD of the UWB pulse@TX] [Recovered data@RX]   Maximum data rate of 90Mbps   1mW power consumption with 90Mbps OOK   Digital clock recovery by the FPGA in the RX   USB interface with PC to handle high bandwidth LPF output FPGA output FCC emission mask
  19. 19. Architecture of Prototype System
  20. 20. Bench Top Test Results
  21. 21. 1. Ex-vivo extracellular action potential recording from a dissected snail brain (A circumoesophageal ring dissected from a H. Aspersa) 2.  Concentric bipolar electrode with 25µm platinum tip with suction 3.  Measured impedance of electrode is 190KΩ at 1KHz. Ex-vivo Recording
  22. 22. In-vitro Recording 1. Snail neurons were cultured on Ayanda MEAs 2. Electrode impedance is 1MΩ. 3. Recording from a cluster of neurons 4. Field potentials were observed.
  23. 23. 1.  4-channel recording IC (cut-down version of 128ch recording IC) 2.  EEG, ECG, EMG 3.  USB2.0 PC interface FPGA USB2.0 FSK FSK PIC Microcontroller Another Prototype System
  24. 24. [A mouse wearing the recording system. Photo was taken at Arizona State University] 1.  Recording electrode implanted in a live mice brain 2.  The impedance of the electrode is 100KΩ. 3.  Extracellular action potentials In-vivo Recording
  25. 25. Human EEG and ECG Recording
  26. 26. Summary & Acknowledgement  Need for versatile wireless recording systems for advanced neuroscience research and neuroprothetics  Challenging requirements in terms of power and area  Need various technologies for the implementation of the system  An example of system implementation  Chip fabrication by National Semiconductor
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